An auditable and source-verified framework for clinical AI decision support: integrating retrieval-augmented generation with data provenance.

Alu FF, Oluwadare S

Open source

DOI
10.3389/frai.2026.1737532
Published
2026
Container
Frontiers in artificial intelligence
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.3389/frai.2026.1737532,
  title = {An auditable and source-verified framework for clinical AI decision support: integrating retrieval-augmented generation with data provenance.},
  author = {Alu FF and Oluwadare S},
  year = {2026},
  journal = {Frontiers in artificial intelligence},
  doi = {10.3389/frai.2026.1737532},
  url = {https://doi.org/10.3389/frai.2026.1737532}
}

RIS

TY  - JOUR
TI  - An auditable and source-verified framework for clinical AI decision support: integrating retrieval-augmented generation with data provenance.
AU  - Alu FF
AU  - Oluwadare S
PY  - 2026
JO  - Frontiers in artificial intelligence
DO  - 10.3389/frai.2026.1737532
UR  - https://doi.org/10.3389/frai.2026.1737532
ER  - 

APA

FF, A., & S, O. (2026). An auditable and source-verified framework for clinical AI decision support: integrating retrieval-augmented generation with data provenance.. Frontiers in artificial intelligence. https://doi.org/10.3389/frai.2026.1737532

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